You might think that computational thinking has something to do with computer science or being tech-savvy, but it actually doesn’t. Computational thinking is an approach to problem-solving that involves critical and logical thinking in order to solve problems, the same way a computer would.
Computational thinking is made up of four main components: decomposition, pattern recognition, abstraction, and algorithmic thinking:
- Decomposition is the task of breaking a big problem into smaller, more manageable problems.
- Pattern recognition is finding similarities within the problem and among other problems, using what has worked before to help you solve the task at hand.
- Abstraction is focusing on only the important details of the problem and ignoring other, lesser important details.
- Algorithmic thinking is the ability to develop a step-by-step guide to solving the problem or a set of rules to solve it.
Computational thinking isn’t just used by computer scientists and programmers. It’s used by people in all kinds of professions, like doctors, carpenters, teachers, and artists.
You’re most likely also using computational thinking subconsciously on a daily basis. Just think about your process when you’re brushing your teeth. At first it sounds like a simple enough task, but in fact, brushing your teeth involves many simple steps. First, you’ll need a toothbrush and toothpaste. You’ll need a sink with cold water. You’ll need to put the toothpaste on the brush. Don’t forget to turn on the water and run your brush underneath. As you see, such a simple activity actually involves many steps, if you miss one step or put one out of order you might end up with a huge mess!
So should kids learn this? My take is yes. Especially if starting homework seem like a battle. Or are they brimming with ideas yet unsure of how to execute them? Do they leave a trail of unfinished projects in their wake? While kids are inherently curious, they lack an innate process of structuring their thinking.
Computational thinking is a problem solving process that could be useful. While the challenges kids encounter may change, the steps of the process remain constant so there’s no guessing at where to start. By structuring their thinking, kids will be able to approach problems in an effective way and dive into finding a solution. You can facilitate opportunities for your kids to learn this consistent approach for tackling problems.
Programming is a great way to help kids learn technical skills and also expose them to computational thinking. It allows them explore and understand the world around them, making it easier for them to learn.
Say your child is trying to make a Hopscotch game where the hero avoids obstacles and earns points for grabbing cheese. Deciding where to start may be overwhelming, but if they apply computational thinking, they’ll know the first step is to break down the problem into smaller pieces: the background, the hero, the obstacles, the cheese, and the points tally.
Once your child breaks the problem into parts, they can example the pieces and search for similarities. If each obstacle moves from right to left, they share that direction in common. Interesting! Maybe they can share the same code. When your child makes these connections, they can assign the obstacles step by step rules, like “when the game starts, change x position by -400.” Repeat that line of code forever and every obstacle will move across the screen from left to right. Done with obstacles? On to the next piece!
And it might help them in the future. Over the past few decades, we’ve seen the impact that computers and automation have had on manufacturing. Workers in manufacturing have felt these changes most keenly. Robotic hands, not human ones, now fasten the lids on our beer bottles and spray paint our cars.
Advances in computer processing power and internet connectivity mean that our service sector is affected in the same way. Travel agents, bankers, sales assistants and even doctors and lawyers are seeing the tasks they used to perform replaced by programs and machines which do their jobs faster, cheaper and sometimes more accurately.
The scale of this challenge is enormous. Economists Carl Benedikt Frey and Michael Osbourne predict that in the US, 47% of existing jobs are under threat from automation. Unchecked, automation will destroy many skilled, middle-income jobs and push more of the middle class into insecure, unskilled work. The winners out of these changes will be those who are able to use machines to advance and enhance their skill sets.
By way of illustration, in September the Seattle-based tech company Sewbo got a robot to successfully stitch a T-shirt from scratch, achieving, it said, ‘the long-sought goal of automation for garment production.’
Evidence seems to be mounting that employment opportunities in the decades to come are likely to be heavily concentrated in the digital and engineering spheres. Topping the list of the World Economic Forum’s essential skills for joining the workforce in what it calls the ‘Fourth Industrial Revolution’ is ‘complex problem solving.’
As our economies and workplaces – not to mention our social lives, culture and entertainment – come to rely more and more on an ever-evolving software infrastructure, problems-solving using computational thinking could prove the ultimate transferable skill. But it’s an invaluable competence for children to develop whatever their futures hold.
Check out my related post: How to encourage flexible thinking in kids?